- author = "Kenji Tamura and Atsuko Mutoh and Tsuyoshi Nakamura and Hidenori Itoh",
- title = "Virus-evolutionary linear genetic programming",
- journal = "Electronics and Communications in Japan",
- year = "2008",
- volume = "91",
- number = "1",
- pages = "32--39",
- note = "Translated from Denki Gakkai Ronbunshi, Vol. 126-C, No. 7, July 2006, pp. 913--918",
- keywords = "genetic algorithms, genetic programming, Virus-Evolutionary Linear Genetic Programming, schema, linear representation, coevolution, virus theory of evolution",
- publisher = "Wiley Periodicals",
-
URL = "
https://zh.art1lib.com/book/1268426/ecd361",
-
URL = "https://onlinelibrary.wiley.com/doi/abs/10.1002/ecj.10030",
-
DOI = "
doi:10.1002/ecj.10030",
- size = "8 pages",
- abstract = "Many kinds of evolutionary methods have been proposed. GA and GP in particular have demonstrated their effectiveness in various problems recently, and many systems have been proposed. One is Virus-Evolutionary Genetic Algorithm (VE-GA), and the other is Linear Genetic Programming in C (LGPC). The performance of each system has been reported. VE-GA is the coevolution system of host individuals and virus individuals. That can spread schema effectively among the host individuals by using virus infection and virus incorporation. LGPC implements the GP by representing the individuals to one dimension as if GA. LGPC can reduce a search cost of pointer and save machine memory, and can reduce the time to implement GP programs. We have proposed that a system introduce virus individuals in LGPC, and analyzed the performance of the system on two problems. Our system can spread schema among the population, and search solution effectively. The results of computer simulation show that this system can search for solution depending on LGPC applying problem character compared with LGPC.",
-
notes = "Two populations (larger host tree+ virus variable
length linear/subtree) co-evolve.
p33 'strings of the virus population represent subsolutions' ... 'A virus copies its own gene string into a host by infection, while extracting a host substring by incorporation' (several virus individuals replaced by subtree [may not be tree] fragment of host tree)
p34
'A virus searches a portion of host with a matching [whole of virus] structure' (like homologous crossover?)
Two point or one point crossover in host(tree) population.
Two point xo: 'Since the crossover points are chosen in portions with matching structural information, the tree structure is not destroyed.'
Use 6-even parity as expect virus population to learn subsolutions. Ant expected to have no subsolutions.
In English
Chuo Gakuin University, Japan",
